News items are commonly distributed and consumed through online news services. Online news services seek to recommend news items that users are likely to be interested in and therefore likely to view. Typically, popular news items are recommended to users. However, popularity alone may not accurately reflect a user's interest and thus may not accurately predict what items a user will select to view.
News items can also be recommended based on a user's selection history. However, recommending news items solely on a user's selection history fails to account for news trends. For example, during the Olympics, a user may have many selections for sports related items but the user may not have a strong preference for sports. On the other hand, the user may want to view sports related items for exceptional sporting events such as the Olympics.
It would be highly desirable to predict a user's news interest by considering a user's selection history of news items relative to the selections made by a community of users.